The present invention relates to providing recommendations for product purchases based on previous product purchases or other behavior by a customer.
Neonics, Inc. U.S. Pat. No. 4,996,642, describes selectively recommending to a user items such as movies sampled by other users. The recommendations are weighted, based on scalar ratings of the user being close to scalar ratings of other users for some product both have reviewed.
MNI Interactive U.S. Pat. No. 5,583,763 describes a user designating his or her preferred selections as entries in a user's preference list. Entries in the user's list are compared with entries in the other users' lists. When a significant number of matches have been found between two lists, the unmatched entries of the other user's preference list are extracted. Those unmatched entries with a high correlation to the user's preference list are presented to the user as selections in which the user is likely to be interested.
Cendant Publishing U.S. Pat. No. 6,782,370 describes allowing customers to submit goods or services to be used as filter data when providing recommendations based on customer buying history.
Amazon.com U.S. Pat. No. 6,266,649 describes a recommendations service that recommends items to individual users based on a set of items that are known to be of interest to the user, such as a set of items previously purchased by the user. In the disclosed embodiments, the service is used to recommend products to users of a merchant's Web site. The real-time service generates the recommendations using a previously-generated (off-line) table which maps items to lists of “similar” items. The similarities reflected by the table are based on the collective interests of the community of users.
Amazon.com U.S. Pat. No. 6,912,505 describes determining relationships between products by identifying products that are frequently viewed by users within the same browsing session (e.g., products A and B are related because a significant portion of those who viewed A also viewed B). The resulting item relatedness data is stored in a table that maps items to sets of related items. The table may be used to provide personalized product recommendations to users.
Amazon.com U.S. Pat. No. 7,113,917 is similar, relating to items actually selected (e.g., in a shopping cart).